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Histogram Equalization(Image Processing Presentation)

Date post: 02-Dec-2014
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Histogram Equalization in image processing.
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Page 1: Histogram Equalization(Image Processing Presentation)
Page 2: Histogram Equalization(Image Processing Presentation)

Contrast adjustment method by using the image's histogram.Useful for images with backgrounds and foregrounds that are both bright or both dark. It can be used for viewing the bone structure in x-rayi d h t h th t dimages, and photographs that are over or under-exposed in order to get better detail .

Ad t > If th hi t li ti f ti Advantage=> If the histogram equalization function is known, then the original histogram can be recovered. Disadvantage=>It may increase the contrast of Disadvantage=>It may increase the contrast of background noise, while decreasing the usable signal.

Page 3: Histogram Equalization(Image Processing Presentation)

Rather than saying that equalization flattens a histogram, it is more accurate to say that it linearizes the cumulative frequency distribution. q yHistogram equalization redistributes pixel intensities according to the origin ratio of pixel distribution to make the number of pixel distribution to make the number of pixel redistribute into each allowed discrete intensity levels.Histogram equalization doesn’t force the distribution “flat” which means the number of pixel in each intensity levels distributed equally pixel in each intensity levels distributed equally or closely.

Page 4: Histogram Equalization(Image Processing Presentation)
Page 5: Histogram Equalization(Image Processing Presentation)

Row(M)=8Column(N)=8MxN= 64Total number of pixel in this image is 64.Total number of pixel in this image is 64.

P(r)= no of pixel in each intensity value/ Total no of pixelP(52)=1/64

Page 6: Histogram Equalization(Image Processing Presentation)
Page 7: Histogram Equalization(Image Processing Presentation)

60

70No of Pixel

40

50

60

20

30

40

No of Pixel

0

10

0

52 58 60 62 64 66 68 70 72 75 77 79 85 88 94 106

113

126

154

Page 8: Histogram Equalization(Image Processing Presentation)

Value No of pixel P(r)

52 1 1/6455 3 4/64

Value cdf cdf, scaled

71 39 154/64

Value cdf cdf, scaled

106 58 231/64109 59 235/6455 3 4/64

58 6 6/6459 9 9/6460 10 10/64

71 39 154/6472 40 158/6473 42 166/6475 43 170/6476 44 174/64

109 59 235/64113 60 239/64122 61 243/64126 62 247/64

61 14 53/6462 15 57/6463 17 65/6464 9 3/64

76 44 174/6477 45 178/6478 46 182/6479 48 190/64

144 63 251/64

64 19 73/6465 22 85/6466 24 93/6467 25 97/64

83 49 194/6485 51 202/6487 52 206/6488 53 210/6467 25 97/64

68 30 117/6469 33 130/6470 37 146/64

90 54 215/6494 55 219/64104 57 227/64154 64 255/64/

Page 9: Histogram Equalization(Image Processing Presentation)

1.2Equalized Value

0.8

1

0.4

0.6Equalized Value

0

0.2

52 58 60 62 64 66 68 70 72 75 77 79 85 88 94 106

113

126

154

Page 10: Histogram Equalization(Image Processing Presentation)
Page 11: Histogram Equalization(Image Processing Presentation)

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